Exclusive expression of KANK4 promotes myofibroblast mobility in keloid tissues

Keloids are characterized by abnormal wound healing with excessive accumulation of extracellular matrix. Myofibroblasts are the primary contributor to extracellular matrix secretion, playing an essential role in the wound healing process. However, the differences between myofibroblasts involved in keloid formation and normal wound healing remain unclear. To identify the specific characteristics of keloid myofibroblasts, we initially assessed the expression levels of well-established myofibroblast markers, α-smooth muscle actin (α-SMA) and transgelin (TAGLN), in scar and keloid tissues (n = 63 and 51, respectively). Although myofibroblasts were present in significant quantities in keloids and immature scars, they were absent in mature scars. Next, we conducted RNA sequencing using myofibroblast-rich areas from keloids and immature scars to investigate the difference in RNA expression profiles among myofibroblasts. Among significantly upregulated 112 genes, KN motif and ankyrin repeat domains 4 (KANK4) was identified as a specifically upregulated gene in keloids. Immunohistochemical analysis showed that KANK4 protein was expressed in myofibroblasts in keloid tissues; however, it was not expressed in any myofibroblasts in immature scar tissues. Overexpression of KANK4 enhanced cell mobility in keloid myofibroblasts. Our results suggest that the KANK4-mediated increase in myofibroblast mobility contributes to keloid pathogenesis.


Human tissue samples
Samples from keloid, normal scars, and normal skin sample were collected from patients who underwent surgery at the Department of Plastic and Reconstructive Surgery of Nagoya University Hospital (Nagoya, Japan) from 2003 to 2022.The keloid samples used in this study were collected from 57 patients.All patients showed evidence indicating the presence of keloids, including clinical appearance, history, and pathological examination.The normal scar samples (n = 82) were collected from patients without symptoms or clinical appearance of keloids.We further classified normal scar samples into two subclasses: immature scars, i.e., scars that formed within 3 years after injury (n = 72); and mature scars, i.e., scars that formed more than 3 years after injury (n = 10).A single normal skin sample was collected to establish a normal fibroblast cell line from residual donor tissue following reconstructive surgery.Detailed patient information is provided in Table 1 and Supplementary Table 1.The majority of mature and immature scars were obtained from planned surgeries associated with breast reconstructions.Therefore, most scar samples were obtained from the chest of females.The collection of samples for this study was approved by the ethics review committee of Nagoya University Hospital (approval number: 2019-0079-5).Written informed consent was provided by the participants in accordance with relevant guidelines and regulations.Samples were collected from June 10, 2019, to December 28, 2022.Archived samples were used for Immunohistochemical analysis, and the clinical records were reviewed on July 1, 2019.

RNA extraction
Total RNA from the cell lines was extracted using TRIzol (Thermo Fisher Scientific, Waltham, MA, USA).To obtain RNA from clinical tissue samples, frozen sections were stained with anti-TAGLN antibody to visualize TAGLN-positive cells in tissue samples.Subsequently, areas of interest containing TAGLN-positive fibroblasts were manually dissected from unstained serial sections using microtweezers under a magnifier at -30 °C.The total RNA from the obtained tissues was extracted using ReliaPrep RNA Tissue Miniprep System (Promega, Madison, WI, USA).Briefly, tissues were homogenized using a hand homogenizer in TRIzol reagent (Thermo Fisher Scientific) and centrifuged.The supernatant was mixed with isopropanol and passed through a column provided with the kit.After several wash steps and DNase treatment, total RNA was eluted in RNase-free water.All RNA samples were evaluated for quality and quantified using a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific).RNA samples were stored at -20 °C.

RNA-seq
Libraries were constructed using the QIAseq UPX 3′ Transcriptome Kit (QIAGEN, Hilden, Germany) according to the instructions provided by the manufacturer.The samples were analyzed using a NovaSeq 6000 instrument (Illumina, Santa Clara, CA, USA).RNA-seq Analysis Portal 2.0 (QIAGEN) was used to map the sequencing reads to a human reference genome (GRCh38).Data analysis was performed on the RNA-seq analysis portal (QIAGEN).Details of the analysis workflow, experiment summary and quality control are available in the Supplementary Table 4.The raw FASTQ files were deposited in the Gene Expression Omnibus database under accession number GSE245660.mRNA expression data of the GSE113619 and GSE92566 datasets were analyzed.Statistical significance for differential gene expression was determined using a fold change threshold of > 2 and a false discovery rate P-value of ≤ 0.1 when comparing the current study and GSE113619, and a fold change threshold of > 2 and a P-value of ≤ 0.05 when comparing GSE113619 and GSE92566.scRNA-seq data of the GSE163973 dataset were obtained from Gene Expression Omnibus database.Sequence data was reanalyzed in the same manner as the original study 9 .Briefly, sequencing reads were quality assessed and transcripts were mapped to a reference human genome (hg38) and then assigned to individual cells using the Cell Ranger pipeline (10 × Genomics).
From the UMI counting matrices, gene expression levels were normalized and principal component analysis (PCA) was performed.Clustering was then performed on the PCA scores using significant PCs, and cell subpopulations were identified using the Louvain method.Visualization was performed using Uniform Manifold Approximation and Projection (UMAP), and fibroblast subpopulations were identified using cluster-specific marker genes, COL1A1 and COL3A1.

Quantitative reverse transcription polymerase chain reaction (reverse transcription-PCR)
RNA was reverse-transcribed with the Prime Script RT Master Mix (Takara Bio, Shiga, Japan) according to the instructions provided by the manufacturer.TaqMan PCR and SYBR Green quantitative PCR were carried out in triplicate for the target genes.The expression levels of target genes were determined using the delta-delta Ct (cycle threshold) method and normalized to those of glyceraldehyde-3-phosphate dehydrogenase (GAPDH).Oligonucleotide primers of GAPDH for TaqMan PCR assays (Hs.PT.39a.22214836;Integrated DNA Technologies, Coralville, IA, USA) and the primer sets for SYBR Green assays are shown in Supplementary Table 2.

Cell culture
Primary fibroblasts were established as previously described 20 .Samples were collected from two scar tissues (i.e., one from a keloid and another from an immature scar).The dermis was isolated from the epidermis, sectioned into fragments (dimensions: approximately 2 mm × 2 mm) using surgical blades, and digested with 100 units/ ml collagenase type I (Gibco, Carlsbad, CA, USA) at 37 °C for 24 h.The mixture was centrifuged at 1200 rpm for 3 min, the supernatant was discarded, and cell pellets were harvested.Cells were cultured in Dulbecco's modified Eagle's medium (DMEM; Wako, Osaka, Japan) containing 10% fetal bovine serum (FBS; Thermo Fisher Scientific) and 1% penicillin-streptomycin (Wako) at 37 °C in a humidified incubator with 5% CO 2 .The medium was changed every 3 days; when the cells reached 90% confluence, they were split at a 1:2 ratio.The established cell lines were cultured for a maximum of 10 passages.SC10 was established in a previous study 21 and maintained in DMEM/F12 (Wako) supplemented with 10% FBS.TGF-β (#100-21, PeproTech, Cranbury, NJ, USA) was used at a concentration of 10 ng/µl.

Construction of the KANK4 expression vector
A cDNA fragment of human KANK4 (NM_001320269.2) was amplified by PCR using cDNA of primary cultured fibroblasts obtained from a patient with keloid.KOD-Plus-Neo (TOYOBO, Osaka, Japan) was used in this experiment, along with the following primers: 5′-CGA GCA TGC ATC TAG TAT GGA GAA GAC AGA TGA GAT -3′ and 5′-AAT AGG GCC CTC TAG CTA CAG CCC CAG GGA CCT-3′.The DNA fragment was subsequently inserted into a pcDNA3 vector (Thermo Fisher Scientific) containing enhanced green fluorescent protein (EGFP) to construct pcDNA3-EGFP-KANK4.The KANK4 sequence in the construct was verified by Sanger sequencing.The pcDNA3-EGFP vector was used as a control.The human KANK4 (NM_181712.5)expression vector was kindly provided by Dr. Kiyama (Kyushu Sangyo University, Japan) 13,14 .

Cell manipulation
Primary fibroblasts were seeded in six-well plates at a density of 2 × 10 5 cells/well for 24 h before transfection using the KANK4 vector.Cells were transfected with 2.5 µg of pcDNA3-EGFP or pcDNA3-EGFP-KANK4 using Lipofectamine 3000 (Thermo Fisher Scientific) for 48 h.Thereafter, cells were plated for migration assay or proliferation assays.After transfection, SC10 cells were trypsinized and resuspended in phosphate-buffered saline, and subjected to fluorescence activated cell sorting (FACS) analysis with FACSMelody (Becton & Dickinson, Franklin Lakes, NJ, USA).GFP-positive cells were collected and cultured for 7 days to be used in further experiments.

Transwell migration assay
Migration assays were performed using chambers with membranes containing 8-μm pore Cell Culture Inserts (CORNING, Corning, NY, USA).The lower chambers were filled with DMEM containing 20% FBS.At 48 h after vector transfection, 1 × 10 5 cells were seeded into the upper chamber containing medium without FBS.
After 24 h of incubation, cells that had migrated and attached to the bottom membrane were stained with 0.1% crystal violet.Stained cells were counted in four randomly selected fields in each well using the ImageJ software.

Cell proliferation assay
Cells were seeded in 96 well plates at a density of 5 × 10 4 cell/well.Cell growth was assessed using Cell Count Reagent SF (Nacalai Tesque, Kyoto, Japan).

Statistical analysis
Data are presented as the mean ± standard deviation.P-values < 0.05 indicate statistically significant differences.Differences between two groups were compared using the unpaired t-test.One-way analysis of variance was used for multiple comparisons.All reported P-values were two-tailed.Statistical analyses were performed using the GraphPad Prism version 9 software (GraphPad Software, San Diego, CA, USA).

Myofibroblasts characteristics varied between normal scars and keloids
Initially, we conducted immunohistochemical analysis focusing on representative myofibroblast markers α-SMA 22 and TAGLN 23 to examine the distribution of myofibroblasts within normal scar and keloid samples (n = 63 and 51, respectively).Notably, α-SMA-and TAGLN-positive myofibroblasts were abundantly present in both normal immature scar and keloid samples.In contrast, such myofibroblasts were not found in mature scar samples (Fig. 1a,b).Furthermore, we calculated the ratio of the myofibroblast-positive area to the total scar area (Supplementary Fig. 1).The areas of α-SMA-positive or TAGLN-positive myofibroblasts in keloid tissues were larger than those observed in mature and immature scar tissues (P < 0.001) (Fig. 1c,d, left panel).Comparison of mature and immature scar tissues revealed more significant difference in the area of TAGLN-positive myofibroblasts than in that of α-SMA-positive myofibroblasts (P < 0.05 and P = 0.2916, respectively).In keloid samples, the duration of disease (< 3 years vs. > 3 years) did not influence the expression of α-SMA and TAGLN (Fig. 1c,d, right panel).Next, we quantified the thickness of the scar tissue.Keloid samples showed a considerably thicker disease area compared with immature or mature scars (P < 0.001) (Fig. 1e, left panel).Among keloid samples, there was no difference in the thickness of the disease area based on the duration of disease.
These results suggested that the number of α-SMA-and TAGLN-positive myofibroblasts in normal scars diminishes over time after injury.In contrast, the widely distributed α-SMA and TAGLN-positive myofibroblasts

RNA-seq reveals the distinct characteristics of keloid myofibroblasts
Next, we analyzed differences in the transcriptome of myofibroblasts between keloids and immature scars.It has been reported that TAGLN is a better marker of smooth muscle differentiation than α-SMA in myofibroblasts 24,25 .Therefore, we collected the TAGLN-positive area from three keloid samples and two immature scar samples, and performed RNA-seq (Fig. 2a, Supplementary Fig. 2, Supplementary Table S1).We found that 112 genes were significantly upregulated and 108 genes were downregulated in keloid samples compared with immature scar samples (fold change > 2, false discovery rate P-value ≤ 0.1) (Fig. 2b).Furthermore, we analyzed the public RNA-seq dataset of keloids samples obtained from keloid-prone patients (n = 8) and immature scar samples from healthy individuals (scars 42 days after injury, n = 6) (GSE113619) 26 .This analysis revealed 192 upregulated genes and 222 downregulated genes in keloids compared with immature scars.Furthermore, we compared the results obtained from the analysis of these two datasets and identified an overlap of six upregulated and two downregulated genes (Fig. 2c, Table 2).We also obtained data from another dataset (GSE92566), which included four keloid samples and three normal skin samples derived from keloid-prone patients.A microarray platform was utilized for this analysis.Among the 770 significantly upregulated genes and 1120 downregulated genes in keloids from GSE92566, 18 upregulated genes and 11 downregulated genes overlapped with those detected in GSE113619 (fold change > 2, P-value ≤ 0.05) (Supplementary Table S3).Analysis of these three datasets (i.e., current RNA-seq, GSE113619, and GSE92566) showed recurrent upregulation of OPCML, S100A7, KANK), and protein tyrosine phosphatase receptor type D (PTPRD).

KANK4 protein was specifically expressed in keloid myofibroblasts
We sought to verify whether the proteins of the six genes that characterize the TAGLN-positive areas of keloids (Fig. 2d) were expressed by fibroblasts in the tissue of keloids and immature scars.OPCML exhibited the greatest upregulation among those genes in keloids (Table 2).We performed immunohistochemical analysis of OPCML in keloids and immature scars, and found that fibroblasts in both tissues were not stained with OPCML (Supplementary Fig. 3a).In keloids, only sebaceous glands were slightly stained with OPCML.
S100A7 and S100A8 exhibited the second and third greatest upregulation in keloids, respectively.S100 refers to a family of proteins expressed in different tissues and cells.According to the scRNA-seq data in the Human Protein Atlas (https:// www.prote inatl as.org/), S100A8 is mostly expressed in keratinocytes and macrophages in skin, while S100A7 is expressed in fibroblasts and keratinocytes.Therefore, we conducted an immunohistochemical analysis of S100A7 using the same set of samples.We found that cutaneous appendages, such as sebaceous glands and hair follicles in keloid tissues, were stained with S100A7.However, fibroblasts were not stained in both keloids and immature scars (Supplementary Fig. 3b).
Next, we focused on KANK4 (i.e., one of the upregulated genes in keloids).Immunohistochemical analysis showed that KANK4 protein was mostly expressed in TAGLN-positive myofibroblasts in keloid tissues (Fig. 3a,b).Interestingly, TAGLN-negative fibroblasts did not express KANK4 in keloid samples (Supplementary Fig. 3c).Contrarily, in immature scars, KANK4 was not expressed in any myofibroblasts.To the quantify the KANK4positive area, we initially binarized the stained areas of TAGLN and KANK4 in consecutive sections into black and white with a threshold.Subsequently, we calculated the stained area (Fig. 3a,b).Our findings revealed a significantly higher ratio of KANK-positive area to the TAGLN-positive area in keloids samples compared with immature scar samples (P < 0.01) (Fig. 3c).Most of the α-SMA-positive fibroblasts also exhibited positive expression of KANK4 (Fig. 3d).
Indeed, scRNA-seq data of keloid and normal scar fibroblasts (GSE163973) showed the presence of TAGLNpositive myofibroblasts in both types of fibroblasts.Of note, KANK4-positive fibroblasts are distinct from normal scar fibroblasts (Supplementary Fig. 3d,e).
These data indicate that myofibroblasts in keloids represent distinct cell populations compared with those found in immature scars, as inferred from the pattern of KANK4 expression.

Upregulation of KANK4 promoted cell mobility in skin fibroblasts
We established fibroblasts from immature scar and keloid tissues to investigate the function of KANK4 in these cells.The expression levels of TAGLN and KANK4 tend to be higher in keloid fibroblasts (n = 10) versus immature scar fibroblasts (n = 13) (P = 0.06 and 0.06, respectively) (Fig. 4a).Interestingly, the expression of collagen type I alpha 2 chain (COL1A2) was not significantly different between keloid fibroblasts and immature scar fibroblasts (P = 0.23) (Fig. 4a).Actin alpha 2 (ACTA2, gene which code α-SMA) and TAGLN are well-established genes; their expression is upregulated by TGF-β in fibroblasts.Therefore, we treated fibroblasts established from normal skin (NFB1), immature scar (FB1) and keloid (FB2 and FB3) tissue with TGF-β, and assessed the mRNA expression levels of these genes.ACTA2 and TAGLN expression was upregulated in all types of fibroblasts after stimulation with TGF-β.KNAK4 expression was also upregulated by TGF-β in these fibroblasts; however, the increase in KANK4 expression was markedly more significant in keloid fibroblasts (P = 0.30 and 0.04 in FB2 and FB3, respectively) versus immature scar fibroblasts (Fig. 4b, Supplementary Fig. 4a).To understand the function of KANK4 in keloid fibroblasts, we overexpressed KANK4 in the established immature fibroblasts (FB1) and keloid fibroblasts (FB2, FB3) (Supplementary Fig. 4b).Since the expression level of KANK4 was very low without TGF-β stimulation (Fig. 4b), we used keloid fibroblasts for overexpression study.The results of the migration assay showed that KANK4 overexpression promoted cell mobility without affecting the rate of cell proliferation rate in both FB1, FB2 and FB3 (P < 0.0001, 0.0007, and 0.034, respectively) (Fig. 4c and Supplementary Fig. 4c).Next, we knockdown KANK4 with siRNA and examined the cell mobility (Supplementary Fig. 4d).Although the expression levels of KANK4 are low in stable condition, the cell mobility was significantly affected by KANK4 knockdown (Supplementary Fig. 4e).Interestingly, KANK4 overexpression did not have any impact of collagen expression (COL1A and COL3A1) (Supplementary Fig. 5a).
We utilized immortalized endometrial fibroblasts, SC10, for further study because our primary fibroblasts were unable to culture for a prolonged period after transfection with the overexpression vector 21 .SC10 are considered as myofibroblasts and express TAGLN.Following transfection with either pcDNA3-EGFP or pcDNA-EGFP-KANK4, we sorted GFP-positive cells using FACS and seeded them for migration assays (Supplementary Fig. 5b).The KANK4-overexpressing cells exhibited significantly increased mobility (P < 0.0001); nevertheless, there was no difference observed in cell proliferation (Supplementary Fig. 5c,d).
Thus far, two different isoforms of KANK4 have been reported, namely NM = 181,712.5(isoform 1) and NM_001320269.2(isoform 2).Isoform 2 lacks one exon and is shorter compared with isoform 1 (Supplementary Fig. 6a).Primer set 1 of KANK4 (amplification of the long isoform) was used in our clinical samples and cell line studies (Figs.2d, 4a,b).Therefore, we also examined the expression of KANK4 in clinical samples using Primer set 2 (amplification of the short and long isoforms) (Supplementary Fig. 6a).The result of qPCR using Primer set 2 revealed that KANK4 expression was significantly higher in keloid tissue versus immature scar tissue (Supplementary Fig. 6b).Interestingly, the ratio of Primer set 2 to Primer set 1 was higher in keloid samples compared with immature scar samples (Supplementary Fig. 6c), suggesting that the shorter isoform of KANK4 is expressed more abundantly in keloid tissue.
Since we used the isoform 2 KANK4-overexpression vector (KANK4-vector in Supplementary Fig. 6a), we also employed the isoform 1 KANK4-overexpression vector (KANK4-full) and validated its impact on the fibroblasts 13,14 .Overexpression of the KANK4-full-length vector exerted a similar effect on cell mobility in fibroblasts to that observed following overexpression of the KANK4-vector (Supplementary Fig. 6d,e).

Discussion
Deregulation of the normal wound healing processes following injury is considered a cause of keloid formation.Previous studies have identified numerous genes that are differentially expressed between keloids, normal skin, and normal scars.However, the key mechanisms underlying the development of keloids remain partly understood [27][28][29] .Recently, new technologies (e.g., scRNA-seq and spatial transcriptomics) have been used to discover novel therapeutic targets for keloids 9,30,31 .Nevertheless, due to the lack of functional studies on candidate genes, the roles of these genes in keloid formation remain unclear.
Various types of cells are involved in keloid formation; fibroblasts are primarily responsible for producing ECM and play a crucial role in the development of the keloids 4 .Therefore, in the present study, we investigated whether the phenotype of myofibroblasts differs between keloids and immature scars.We performed immunohistochemical staining using two commonly used myofibroblast markers, α-SMA and TAGLN.The results revealed the presence of α-SMA-and TAGLN-positive areas in immature scars and keloids, but not in mature scars.Additionally, the thickness of the layer which myofibroblasts were present was greater in keloids compared with immature scars.Further RNA-seq analysis, using RNA extracted from TAGLN-positive areas in keloid and immature scars, identified keloid-specific genes that showed differentially expression in these myofibroblasts.While previous scRNA-seq of keloid fibroblasts uncovered significant heterogeneity within fibroblasts populations, our analysis revealed consistently identifying the upregulation of several key genes, including KANK4, across not only our RNA-seq data but also two different datasets.
KANK4 was upregulated in skin fibroblasts obtained from old donors (average age: 60 years) compared with young donors (average age: 25 years) 32 .Studies revealed an association between KANK4 and Rho GDP dissociation inhibitor α (ARHGDIA), which mediates the activation of the Rho pathway.Knockdown of KANK4 in older fibroblasts increased RhoA activity and reduced the contractile capacity.A previous study showed that https://doi.org/10.1038/s41598-024-59293-zwww.nature.com/scientificreports/

Figure 1 .
Figure 1.Distribution of myofibroblasts of normal scars and keloids.(a,b) Representative image of immunohistochemical analyses for α-SMA (a) and TAGLN (b) in mature scars, immature scars and keloids.Rectangle areas are magnified in the second row (magnification 40×).Scale bar: 100 μm.(c) Left panel: Percentage of areas with α-SMA-positive myofibroblasts in the whole scars.Scars were grouped as mature scars (n = 10), immature scars (n = 51), and keloids (n = 44).Right panel: Keloid samples were further divided into two subgroups, namely those formed within 36 months after injury (n = 24) and those formed after 37 months (n = 16).Error bars show the mean ± SD.P-value was determined suing the two-tailed t-test.***P < 0.001.(d) Left panel: Percentage of areas with TAGLN-positive myofibroblasts in the whole scars.Scars were grouped as mature scars (n = 10), immature scars (n = 53), and keloids (n = 51).Right panel: Keloid samples were further divided in to two subgroups, namely those formed within 36 months after injury (n = 27) and those formed after 37 months (n = 19).Error bars show the mean ± SD.P-value was determined using the twotailed t-test.*P < 0.05, ***P < 0.001.(e) Left panel: Thickness of scar tissue.Distances was determined by measuring the perpendicular distance from the bottom of the epidermal basal layer to the adipose layer.Five different fields were used for measurement in each sample, and average distance was used for calculation.Scars were grouped as mature scars (n = 10), immature scars (n = 53) and keloids (n = 51; left).Right panel: Keloid samples were further divided into two subgroups, namely those formed within 36 months after injury (n = 27) and those formed after 37 months (n = 19).Error bars show the mean ± SD.P-value was determined using the two-tailed t-test.***P < 0.001.α-SMA α-smooth muscle actin, ns not significant, SD standard deviation, TAGLN transgelin.

Table 1 .
Clinical background of keloid patients and normal scar controls.Ages and durations after injury are presented as the mean ± standard deviation (SD).

Table 2 .
Differentially expressed genes from RNA-seq analysis.FC fold change, FDR false discovery rate.